Garage Biotech: New drugs using only a computer, the internet and free online data
May 5, 2016

Garage startup (credit: Chase Dittmer)
By David Glance
Director of UWA Centre for Software Practice, University of Western Australia
Pharmaceutical companies typically develop new drugs with thousands of staff and budgets that run into the billions of dollars. One estimate puts the cost of bringing a new drug to market at $2.6 billion with others suggesting that it could be double that cost at $5 billion.
One man, Professor Atul Butte, director of the University of California Institute of Computational Health Sciences, believes that like other Silicon Valley startups, almost anyone can bring a drug to market from their garage with just a computer, the internet, and freely available data.
In a talk given at the Science on the Swan conference held in Perth this week, Professor Butte outlined the process for an audience of local and international scientists and medics.
The starting point is the genetic data from thousands of studies on humans, mice and other animals, that is now freely available on sites from the National Institute of Health and the European Molecular Biology Laboratory. The proliferation of genetic data from experiments has been driven by the ever decreasing cost of sequencing genetic information using gene chip technologies.
Professor Butte, students, and research staff have found a range of different ways of using this data to look for new drugs. In one approach, they have constructed a map of how the genetic profiles of people with particular diseases are related to each other. In particular, to look for diseases with very similar genetic profiles. Having done that, they noticed that the genetic profile of people with heart conditions were very closely related to that of the much rarer condition of muscular dystrophy. What this potentially suggested was that drugs that work for one condition could potentially work in the other. This process of discovering other uses of drugs, called “drug repositioning”, is not new. Drugs like Viagra were originally used for treatment of cardiovascular conditions. The difference is that Viagra’s repositioned use resulted from the observation of side-effects in patients taking the drug for its original intended purpose.
Professor Butte on the other hand is using “Big Data” and computers to show that given the close relationship in the genetic profile of two diseases, the potential cross-over effect of drugs working for one condition working in another.
Still in the garage, the next step from discovering a potential drug is to test if it actually works in an experimental setting on animals. Here again, Professor Butte has turned to the internet and sites like Assay Depot. This is a site, structured like Amazon, from which a researcher can order an experiment to be carried out to test a drug on a range of animal models. It is literally a case of choosing the experiment type you want, adding it to a shopping cart, paying by credit card and getting the experimental results mailed back in a few weeks time. “Shoppers” are given the choice of laboratory they want to use, including a choice of which country the lab is based.
Once a new use for a drug has been shown to work in an animal model, the next step would be to test the drug in humans, get approval for the use of the drug for that condition and then finally take the drug to market.
In California where Professor Butte works, this has involved spinning out companies with money from investors, a process that he and his students have done after the discovery of new uses for several drugs.
As with cloud computing and cloud labour, “cloud research” works because services can be sourced inexpensively from laboratories that have expertise in particular areas. In one case, Professor Butte related a story of needing to see if a drug would cure inflammatory bowel diseases in rats which involved performing colonoscopies on the animals. This expertise and equipment was available somewhere in the world, made accessible through a simple online shopping interface.
The entire process outlined for this type of drug discovery, testing and commercialisation, radically changes the nature of how quickly and cheaply, new drugs can be brought to market to treat conditions for which there would still be few options.
None of this would be possible without the sharing of data and it highlights how the growth of availability of open research data will be able to fuel a range of uses that would not have been foreseen when the individual experiments were being carried out.
Source: The Conversation
Comments (6)
by neilrued
Hi,
I don’t think we should shy away from this technology because the benefits will far outweigh the risks.
One area the article did not give much detail on, is on how will the drugs be synthesized? Are there computer programs, with the appropriate robotics that can allow any reasonably smart person to assemble the required medicinal polymers?
Would it be feasible to adapt this technology, to permit a research team in a remote location to fabricate any needed medication in case of a medical emergency? For example having a supply of generic basic biologically friendly polymers, could the medic/paramedic, nurse or doctor synthesize antibiotics, anti venoms, or other life saving medications in the event of an emergency? Could such a technology be used in a future mission to Mars, where instead of taking an entire pharmacy, the crew have a stock of basic pharmaceuticals that may be combined in different ways to produce any required life saving medications?
by Scribblerlarry
I can see a huge underground black market developing from this. It would most likely come as products finish the lab animal testing before the start of any extremely expensive human testing.
Information about the availability of such products could easily be spread through both the regular internet and the dark internet.
by DevilDocNowCiv
eldras,
The dangers are always there, but this article notes using standard proceedures of first animal testing and finally human testing, so the most modern safety measures are still in place. However, no question, someone could use the cheaper process to stop at an early stage of animal testing and tell his/her buddies “lets jump on this, put it on the internet, and let the market be our human test lab where we get paid rather than we pay and wait. Our shell company will take the risk, and we get the profits.” So, yes eldras, caveat emptor should be taught in both grade and high school now that “the market” is in the pocket of every student with a smartphone.
by 'eldras
This was an early prediction of modern futurists, and wasn’t expected for another 10 years. As this links to home robotics many inventions will emerge…and many dangers.
It is still dangerous to use drugs whose reasons for success are unknown, because they may be new to the evolutionary soup.
by cloudswrest
This sort of contract laboratory services was one of the main plot elements of Vernor Vinge’s “Rainbows End”, although the laboratory services were much more automated in the novel.
by DevilDocNowCiv
Ah, Vernor. A moment of lowered head and respectful silence for the “Sing” creator. Back! Yes, among the many things he got right are tech allowing widely dispersed drug creation. Thus great! Poor kids far from big hospitals get their drugs. And bad, ’cause we then get superCrack anywhere and everywhere.
And what Vern missed was our sad, dysfunctional widespread adoption by the anti-tech movement who work against GM almost anything of “the precautionary principle.” Cautiously pre-emptively deny adopoption of a given tech until you can prove it absolutely safe. Sounds super great to some – why not be cautious?
Fine, then stop eating almost everything you eat, use of most vitamins, and drinking of most bottled water and all tapwater. Thats how dysfunctional the “precautionary principle” is if applied widely.
For instance, with GM the “thoughtful” objecction is that even though GM makes specific, small alterations and zero harm can be shown, or at least much less harm that before any documented US GM product, the precautionary complaint is that because an alteration is made in the food genome we wont know for a long time what dangers may show up, someday due to that tiny, limited alteration.
So following my objoction, now apply that to the food supply in general. We have used the process widely of bombarding seeds with radiation and gene altering chemicals. We then plant the seeds in marked plots. The many seeds have seen dramatic, widespread genetic alteration of an unknown nature, in comparison with GM alteration.
The resulting growth is compared with each other and current crops. Any desireble mutations are “groomed” and “fine tuned” for the table. A much more chancy issue per the precautionary principle than GM. Sadly, most of the anti -GM folks are solidly emotionally bound to the cause, and a logically valid arguement like this is like shooting a tank with a .22 gauge rabbit or squirrel rifle.